Work Experience
Amazon WW Grocery
Seattle, WASoftware Development Engineer IIOctober 2023 – Present
- •HAWK: Predictive Operations Intelligence — Multi-site operational intelligence platform with subprocess-level bottleneck detection, comparative performance benchmarking, and predictive ETAs.
- •Architected hybrid system (SNS/Lambda, time-series + NoSQL, SageMaker + LLM) achieving sub-200ms latency, reducing MTTR by ~35% and process variance by 40%.
- •Built time-series analytics engine surfacing cyclical patterns; increased manager adoption from 30% to 85% and reduced unplanned overtime by 25%.
- •Grocery Identification Microservice — Owned end-to-end design of near real-time event processing service consuming 10K-100K inventory updates/day.
- •Built scalable queue-based infrastructure with serverless compute and retry logic, enabling 6+ services to consume events with zero code changes.
- •Led 3 engineers through system design reviews, implementation, code reviews, automated testing, deployment, and monitoring.
- •Multi-Region Data Migration — Re-architected inventory datastore from relational to NoSQL (DynamoDB), achieving 10x throughput scalability while reducing infrastructure costs by 10%.
- •Designed and executed zero-downtime migration of 10M+ records with < 5 minutes downtime and comprehensive validation across multiple regions.
Amazon Physical Stores
Seattle, WASDE to SDE IIJuly 2021 – October 2023
- •Cloud & Infrastructure Migration — Migrated high-traffic backend microservice to serverless Lambda + API Gateway architecture, reducing infrastructure costs by 50%.
- •Developed migration scripts for 100+ fulfillment centers worldwide, orchestrating SKU data transfer and enabling full deprecation of legacy warehouse management system.
- •Tool Modernization & Performance — Led migration of 3+ internal tools from AngularJS to React, designing incremental rollout with feature flags for safe, reversible production deployments.
- •Optimized web application performance by 49% (5s to 2.4s) through bundle analysis and dependency optimization, saving ~$68 per user in operational costs.
AI & Automation Interest
Growing interest in exploring how AI and automation can enhance operational systems, developer productivity, and system intelligence.
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LLM Integration
Integrating Claude, GPT models, and other LLMs into systems for intelligent automation and decision-making
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Workflow Automation
Building automated systems using modern AI tools to reduce manual toil and improve operational efficiency
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Intelligent Agents
Designing agentic systems that can make decisions, take actions, and adapt based on operational context
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AI-Driven Operations
Applying AI to operational intelligence, predictive analytics, anomaly detection, and system optimization
Education
2019 - 2021 · University of Florida
M.S., Computer and Information Sciences
Gainesville, FL
Skills
Languages
EnglishNative
Soft Skills
System DesignLeadershipProblem SolvingE2E OwnershipBias for ActionCross-functional CollaborationDealing with Ambiguity
Tech Stack
Languages
JavaKotlinPythonJavaScriptTypeScriptSQL
Cloud & Infrastructure
AWS (Lambda, API Gateway, DynamoDB, SQS, SageMaker, EC2)DockerKubernetesCI/CD
Databases
DynamoDBPostgreSQLTime-series DBsElasticsearch
AI Tools
Claude APIGitHub CopilotSageMakerPrompt EngineeringLLM Integration
Monitoring
CloudWatchX-RayApplication Performance MonitoringCustom Metrics